This paper presents an innovative way of using the two-dimensional (2-D) Fourier transform for speech enhancement. The blocking and windowing of the speech data for the 2-D Fourier transform are explained in detail. Several techniques of filtering in the 2-D Fourier transform domain are also proposed. They include magnitude spectral subtraction, 2-D Wiener filtering as well as a hybrid filter w...

In this paper we study an LMS-DFE. We use the ODE framework to show that the LMS-DFE attractors are close to the true DFE Wiener filter (designed considering the decision errors) at high SNR. Therefore, via LMS one can obtain a computationally efficient way to obtain the true DFE Wiener filter under high SNR. We also provide examples to show that the DFE filter so obtained can significantly out...

The aim of this paper is to extend our previous work on a novel and recent class of nonlinear filters called Spline Adaptive Filters (SAFs), implementing the linear part of the Wiener architecture with an IIR filter instead of an FIR one. The new learning algorithm is derived by an LMS approach and a bound on the choice of the learning rate is also proposed. Some experimental results show the e...

We present a novel framework for denoising signals from their compact representation in multiple domains. Each domain captures, uniquely, certain signal characteristics better than others. We define confidence sets around data in each domain and find sparse estimates that lie in the intersection of these sets, using a POCS algorithm. Simulations demonstrate the superior nature of the reconstruc...

Two-dimensional (TD) adaptive filtering is a technique that can be applied to many image, and signal processing applications. This paper extends the one-dimensional adaptive filter algorithms to TD structures and the novel TD adaptive filters are established. Based on this extension, the TD variable step-size normalized least mean squares (TD-VSS-NLMS), the TD-VSS affine projection algorithms (...

Conventionally, radiographic images have low contrast due to less illumination of the light. X-Ray imaging is one of the least expensive, easy to read method used by most of the doctors and radiologists. A method based on dual tree complex wavelet transform (DTCWT), contrast limited adaptive histogram equalization (CLAHE) and Wiener filter is proposed for enhancing the visual quality of the X-R...

A novel approach to image-denoising based on the shapeadaptive DCT (SA-DCT) is presented. The anisotropic LPAICI technique is used in order to deÞne the shape of the transform’s support in a pointwise adaptive manner. It means that for each point in the image an adaptive estimation neighborhood is found. For each one of these neighborhoods a SADCT is performed. The thresholded SA-DCT coefÞcient...

Krylov-subspace methods, such as the multistage Wiener filter and conjugate gradient method, are often used for reduced-dimension adaptive beamforming. These techniques do not, however, allow for steering vector mismatch, which is typically present in many applications of interest, including passive sonar. Here, we discuss recently proposed robust methods that do allow for steering vector misma...

Common hybrid video coding standards such as H.263, MPEG-1,2,4 are based on motion compensated prediction. For the motion compensated prediction purpose, displacement vectors with fractional-pel resolutions (e.g. 1/2-pel or 1/4-pel) are used. In order to estimate and compensate fractional-pel displacements, the image signal has to be interpolated. The most popular and very simple interpolation ...